Diabetes mellitus is an incurable chronic disease in which the body does not produce or properly utilize insulin. Insulin is a hormone produced by the pancreas that regulates blood glucose. In particular, when blood glucose levels rise, e.g., after a meal, insulin lowers the blood glucose levels by facilitating blood glucose to move from the blood into the body cells. Thus, when the pancreas does not produce sufficient insulin (a condition known as Type I diabetes) or does not properly utilize insulin (a condition known as Type II diabetes), the blood glucose remains in the blood resulting in hyperglycemia or abnormally high blood sugar levels.
People suffering from diabetes often experience long-term complications. Some of these complications include blindness, kidney failure, and nerve damage. Additionally, diabetes is a factor in accelerating cardiovascular diseases such as atherosclerosis (hardening of the arteries), which often leads to stroke, coronary heart disease, and other diseases, which can be life threatening.
The severity of the complications caused by both persistent high glucose levels and blood glucose level fluctuations has provided the impetus to develop diabetes management systems and treatment plans. In this regard, diabetes management plans historically included multiple daily testing of blood glucose levels, typically by a finger-stick to draw and test blood. The disadvantage with finger-stick management of diabetes is that the user becomes aware of his blood glucose level only when he performs the finger-stick. Thus, blood glucose trends and blood glucose snapshots over a period of time is unknowable. More recently, diabetes management has included the implementation of analyte monitoring systems, such as glucose monitoring systems which use in vivo sensors that continuously or intermittently generate signals indicative of the fluctuation in the analyte levels. Analyte monitoring systems have the capability to continuously monitor a user's glucose levels, and thus have the ability to illustrate not only present glucose levels but a snapshot of glucose levels and glucose fluctuations over a period of time.
Analyte monitoring systems also have the capability to output alarm notifications, such as an audible alarm, to alert the user to a condition that may require medical attention. Such alarms are usually triggered when the blood glucose level of a patient exceed a preset glucose level threshold. Some analyte monitoring systems also include projected alarms that warn the user of an impending high or low glucose level.
The method of calculating the projected alarms varies according to the glucose monitoring system being used. For example, some glucose monitoring systems use the present glucose level and its rate of change (slope) to make a straight-line extrapolation of the glucose value at times in the future. If the glucose value is projected to be above or below a certain threshold within a certain time period, the projected alarm is sounded. The user experience is very much affected by the frequency of the projected alarms.
For example, some analyte monitoring systems only utilize a small sampling of data points to calculate the glucose level rate of change. In other analyte monitoring systems, a high uncertainty value might disqualify an alarm activation even if the probability of a glycemic condition occurring is very high. Furthermore, some analyte monitoring systems assign an arbitrary penalty to missing glucose level data points that increase uncertainty. If ineffective calculation techniques are utilized to calculate the projected glucose level, such as those just described, the analyte monitoring system may output false projected alarms.